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Parametric And Non- Parametric Crop Yield Distributions and Their Effects on All-Risk Crop Insurance Premiums

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  • Turvey, Calum
  • Zhao, Jinhua
Abstract
Normal, gamma and beta distributions are applied to 609 crop yield histories of Ontario farmers to determine which, if any, best describe crop yields. In addition, a distribution free non-parametric kernel estimator was applied to the same data to determine its efficiency in premium estimation relative to the three parametric forms. Results showed that crop yields are most likely to be described by a beta distribution but only for 50% of those tested. In terms of efficiency in premium estimation, minimum error criteria supports use of a kernel estimator for premium setting. However, this gain in efficiency comes at the expense of added complexity.
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Suggested Citation

  • Turvey, Calum & Zhao, Jinhua, 1999. "Parametric And Non- Parametric Crop Yield Distributions and Their Effects on All-Risk Crop Insurance Premiums," Working Papers 244742, University of Guelph, Department of Food, Agricultural and Resource Economics.
    • Handle: RePEc:ags:uguewp:244742
    DOI: 10.22004/ag.econ.244742
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    1. Richard H. Day, 1965. "Probability Distributions of Field Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 47(3), pages 713-741.
    2. Gallagher, Paul W., 1986. "U. S. Corn Yield Capacity and Probability: Estimation and Forecasting with Non-Symmetric Disturbances," Staff General Research Papers Archive 10780, Iowa State University, Department of Economics.
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    5. Antle, John M, 1983. "Testing the Stochastic Structure of Production: A Flexible Moment-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(3), pages 192-201, July.
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    Cited by:

    1. Jing Wang & Feng Fang & Qiang Zhang & Jinsong Wang & Yubi Yao & Wei Wang, 2016. "Risk evaluation of agricultural disaster impacts on food production in southern China by probability density method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(3), pages 1605-1634, September.
    2. Ozaki, Vitor & Campos, Rogério, 2017. "Reduzindo a Incerteza no Mercado de Seguros: Uma Abordagem via Informações de Sensoriamento Remoto e Atuária," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 71(4), December.
    3. Qiujie Zheng & H. Holly Wang & Qing Hua Shi, 2014. "Estimating bivariate yield distributions and crop insurance premiums using nonparametric methods," Applied Economics, Taylor & Francis Journals, vol. 46(18), pages 2108-2118, June.
    4. Tor N. Tolhurst & Alan P. Ker, 2015. "On Technological Change in Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 137-158.
    5. Upmanu Lall & Naresh Devineni & Yasir Kaheil, 2016. "An Empirical, Nonparametric Simulator for Multivariate Random Variables with Differing Marginal Densities and Nonlinear Dependence with Hydroclimatic Applications," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 57-73, January.
    6. Vitor A. Ozaki & Sujit K. Ghosh & Barry K. Goodwin & Ricardo Shirota, 2008. "Spatio-Temporal Modeling of Agricultural Yield Data with an Application to Pricing Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 951-961.
    7. Santeramo, Fabio Gaetano & Maccarone, Irene, 2022. "Analisi storica delle rese agricole e la variabilità del clima: Analisi dei dati italiani sui cereali [Historical crop yields and climate variability: analysis of Italian cereal data]," MPRA Paper 114135, University Library of Munich, Germany, revised 04 Aug 2022.
    8. Vitor Ozaki & Barry Goodwin & Ricardo Shirota, 2008. "Parametric and nonparametric statistical modelling of crop yield: implications for pricing crop insurance contracts," Applied Economics, Taylor & Francis Journals, vol. 40(9), pages 1151-1164.
    9. Lanoue, Christopher & Sherrick, Bruce J. & Woodard, Joshua D. & Paulson, Nicholas D., 2010. "Evaluating Yield Models for Crop Insurance Rating," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61761, Agricultural and Applied Economics Association.
    10. Woodard, Joshua D. & Chiu Verteramo, Leslie & Miller, Alyssa P., 2015. "Adaptation of U.S. Agricultural Production to Drought and Climate Change," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205903, Agricultural and Applied Economics Association.
    11. Lee, Sangjun & Zhao, Jinhua & Thornsbury, Suzanne, 2013. "Extreme Events and Land Use Decisions under Climate Change in Tart Cherry Industry in Michigan," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150568, Agricultural and Applied Economics Association.
    12. Ghahremanzadeh, Mohammad & Mohammadrezaei, Rassul & Dashti, Ghader & Ainollahi, Moharram, 2018. "Designing a whole-farm revenue insurance for agricultural crops in Zanjan province of Iran," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 17(02), January.

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    Keywords

    Crop Production/Industries;

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